Machine learning algorithms generate predictions, recommendations and new content by analyzing and identifying patterns in their training data. These capabilities power widely used technologies such ...

Framework applying Kirchoff’s laws of current flow and voltage changes across circuits can identify lower-energy analog computing approaches for machine learning.

Supervised learning algorithms learn from labeled data, where the desired output is known. These algorithms aim to build a model that can predict the output for new, unseen input data. Let’s take a ...

Machine learning and AI are transforming how businesses operate: improving efficiency, streamlining workflows, establishing consistency, maintaining security and compliance, and creating new ...

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

Three new books warn against turning into the person the algorithm thinks you are. Like a lot of Netflix subscribers, I find that my personal feed tends to be hit or miss. Usually more miss. The ...

Can we ever really trust algorithms to make decisions for us? Previous research has proved these programs can reinforce society’s harmful biases, but the problems go beyond that. A new study shows how ...

Understanding machine learning can help you build recommendation engines or perform data science work. Machine learning may sound relatively old-fashioned in the age of AI, but it remains a valuable ...

A share of stock trades thousands of times each day. Each trade is an individual data point revealing exactly what buyers ...

The FIFA World Cup has seen 'Paul the Octopus' - the famous eight-limbed soothsayer. In this age of AI and machine learning, predicting a World Cup winner has become more refined. Take, for example, ...